Download or read book Concept Formation and Knowledge Revision written by Stefan Wrobel and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fundamental assumption of work in artificial intelligence and machine learning is that knowledge is expressed in a computer with the help of knowledge representations. Since the proper choice of such representations is a difficult task that fundamentally affects the capabilities of a system, the problem of automatic representation change is an important topic in current research. Concept Formation and Knowledge Revision focuses on representation change as a concept formation task, regarding concepts as the elementary representational vocabulary from which further statements are constructed. Taking an interdisciplinary approach from psychological foundations to computer implementations, the book draws on existing psychological results about the nature of human concepts and concept formation to determine the scope of concept formation phenomena, and to identify potential components of computational concept formation models. The central idea of this work is that computational concept formation can usefully be understood as a process that is triggered in a demand-driven fashion by the representational needs of the learning system, and identify the knowledge revision activities of a system as a particular context for such a process. The book presents a detailed analysis of the revision problem for first-order clausal theories, and develops a set of postulates that any such operation should satisfy. It shows how a minimum theory revision operator can be realized by using exception sets, and that this operator is indeed maximally general. The book then shows that concept formation can be triggered from within the knowledge revision process whenever the existing representation does not permit the plausible reformulation of an exception set, demonstrating the usefulness of the approach both theoretically and empirically within the learning knowledge acquisition system MOBAL. In using a first-order representation, this book is part of the rapidly developing field of Inductive Logic Programming (ILP). By integrating the computational issues with psychological and fundamental discussions of concept formation phenomena, the book will be of interest to readers both theoretically and psychologically inclined. From the foreword by Katharina Morik: ` The ideal to combine the three sources of artificial intelligence research has almost never been reached. Such a combined and integrated research requires the researcher to master different ways of thinking, different work styles, different sets of literature, and different research procedures. It requires capabilities in software engineering for the application part, in theoretical computer science for the theory part, and in psychology for the cognitive part. The most important capability for artificial intelligence is to keep the integrative view and to create a true original work that goes beyond the collection of pieces from different fields. This book achieves such an integrative view of concept formation and knowledge revision by presenting the way from psychological investigations that indicate that concepts are theories and point at the important role of a demand for learning. to an implemented system which supports users in their tasks when working with a knowledge base and its theoretical foundation. '

Download or read book Concept formation and knowledge revision written by Stefan Wrobel and published by . This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Information Modelling and Knowledge Bases XI written by Eiji Kawaguchi and published by IOS Press. This book was released on 2000 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the tenth volume in a series on information modelling and knowledge bases. The topics of the articles cover a wide variety of themes in the domain of information modelling, design and specification of information systems and knowledge bases, ranging from foundations and theories to systems construction and application studies. The contributions in this volume represent the following major themes: models in intelligent activity; concept modelling and conceptual modelling; conceptual modelling and information requirements specification; collections of concepts, knowledge base design, and database design; human-computer interaction and modelling; software engineering and modelling; and applications.

Download or read book Machine Learning written by Ryszard S. Michalski and published by Morgan Kaufmann. This book was released on 1994-02-09 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.

Download or read book Knowledge Based Systems Four Volume Set written by Cornelius T. Leondes and published by Elsevier. This book was released on 2000-07-11 with total page 1554 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making. With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.

Download or read book In Order to Learn written by Frank E. Ritter and published by Oxford University Press. This book was released on 2007-07-30 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur.

Download or read book Algorithmic Learning Theory written by Osamu Watanabe and published by Springer Science & Business Media. This book was released on 1999-11-17 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Algorithmic Learning Theory, ALT'99, held in Tokyo, Japan, in December 1999. The 26 full papers presented were carefully reviewed and selected from a total of 51 submissions. Also included are three invited papers. The papers are organized in sections on Learning Dimension, Inductive Inference, Inductive Logic Programming, PAC Learning, Mathematical Tools for Learning, Learning Recursive Functions, Query Learning and On-Line Learning.

Download or read book PRICAI 96 Topics in Artificial Intelligence written by Norman Foo and published by Springer Science & Business Media. This book was released on 1996 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 4th Pacific Rim International Conference on Artificial Intelligence, PRICAI '96, held in Cairns, Queensland, Australia in August 1996. The 56 revised full papers included in the book were carefully selected for presentation at the conference from a total of 175 submissions. The topics covered are machine learning, interactive systems, knowledge representation, reasoning about change, neural nets and uncertainty, natural language, constraint satisfaction and optimization, qualitative reasoning, automated deduction, nonmonotonic reasoning, intelligent agents, planning, and pattern recognition.

Download or read book Classification and Clustering in Business Cycle Analysis written by Ullrich Heilemann and published by Duncker & Humblot. This book was released on 2007-01-18 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of cyclical macroeconomic phenomena is an important field of econometric research. In the recent past, research interests have de-emphasized quantitative forecasting exercises and have addressed the qualitative diagnosis of the relative stance of the economy regarding »upswing«, »recession«, or »boom« periods, i. e. the classification of the state of the economy into a limited number of discrete states. In this context the principal challenge is to reduce the multifaceted and sometimes abundant quantitative information about the business cycle to such qualitative statements in an efficient way. For more than six years this task was the focus of the project »Multivariate determination and analysis of business cycles« within the SFB 475 »Reduction of complexity in multivariate data structures«, funded by the German Research Foundation (DFG). The necessity for complexity reduction is, of course, not unique to business cycle analysis but is studied in many fields and in a number of ways. This broad interest in the reduction of problem dimensionality and in the appropriate combination of data and of theory caused the RWI Essen and the Statistical Department of the University of Dortmund in January 2002 to hold a workshop at the RWI Essen where the findings of this and similar projects were presented and discussed. The present publication collects revised versions of the papers presented at this workshop. Although the workshop took place some five years ago, these papers mark an importent juncture in the development of business cycle research.

Download or read book Knowledge based Systems Advanced Concepts Techniques And Applications written by Spyros Tzafestas and published by World Scientific. This book was released on 1997-06-16 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of knowledge-based systems (KBS) has expanded enormously during the last years, and many important techniques and tools are currently available. Applications of KBS range from medicine to engineering and aerospace.This book provides a selected set of state-of-the-art contributions that present advanced techniques, tools and applications. These contributions have been prepared by a group of eminent researchers and professionals in the field.The theoretical topics covered include: knowledge acquisition, machine learning, genetic algorithms, knowledge management and processing under uncertainty, conflict detection and resolution, structured knowledge architectures, and natural language-based man-machine communication.The Applications include: Real-time decision support, system fault diagnosis, quality assessment, manufacturing production, robotic assembly, and robotic welding.The reader can save considerable time in searching the scattered literature in the field, and can find here a powerful set of how-to-do issues and results.

Download or read book Industrial and Engineering Applications or Artificial Intelligence and Expert Systems written by Takushi Tanaka and published by CRC Press. This book was released on 1997-01-30 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume includes the proceedings from Proceedings of the Ninth International Conference Fukuoka, Japan, June 4-7, 1996. This work represents a broad spectrum of new ideas in the field of applied artificial intelligence and expert systems, and serves to disseminate information regarding intelligent methodologies and their implementation in solving various problems in industry and engineering.

Download or read book Data Analysis and Information Systems written by Hans-Hermann Bock and published by Springer Science & Business Media. This book was released on 2013-03-07 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents 45 articles dealing with theoretical aspects, methodo logical advances and practical applications in domains relating to classifica tion and clustering, statistical and computational data analysis, conceptual or terminological approaches for information systems, and knowledge struc tures for databases. These articles were selected from about 140 papers presented at the 19th Annual Conference of the Gesellschaft fur Klassifika tion, the German Classification Society. The conference was hosted by W. Polasek at the Institute of Statistics and Econometry of the University of 1 Basel (Switzerland) March 8-10, 1995 . The papers are grouped as follows, where the number in parentheses is the number of papers in the chapter. 1. Classification and clustering (8) 2. Uncertainty and fuzziness (5) 3. Methods of data analysis and applications (7) 4. Statistical models and methods (4) 5. Bayesian learning (5) 6. Conceptual classification, knowledge ordering and information systems (12) 7. Linguistics and dialectometry (4). These chapters are interrelated in many respects. The reader may recogni ze, for example, the analogies and distinctions existing among classification principles developed in such different domains as statistics and information sciences, the benefit to be gained by the comparison of conceptual and ma thematical approaches for structuring data and knowledge, and, finally, the wealth of practical applications described in many of the papers. For convenience of the reader, the content of this volume is briefly reviewed.

Download or read book Computers As Assistants written by Peter Hoschka and published by CRC Press. This book was released on 2021-01-31 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer systems based on the notion of the computer as assistant have recently become the focus of intense interest. The expanding role of the computer in everyday life and the growing number of untrained users make it necessary to think about new ways of dividing labor between humans and machines. Future systems must take on more tasks and perform them more competently and autonomously than existing systems. If they are to be adequately flexible and responsive to complexity, they cannot automate their performance completely. The aim of designers should be to create computer systems with capabilities similar to those of good assistants in the real world. Effective assistance has many characteristics. An assistant is expected to be competent in some domains of expertise, to know the limits of his/her knowledge, to be able to process inexact instructions from clients, to adjust to and learn from them, to explain his/her behavior and suggestions, and to support clients in communication and cooperation with other people. This book believes that such capabilities can be built into computer systems. To that end, the chapter contributors discuss the concepts and methods--particularly from the fields of artificial intelligence and computer-supported cooperative work (CSCW)--that they have drawn from to develop successful system prototypes. They present several of these prototypes including assistants for graphics design, knowledge discovery in data bases, coordination support, organizational memory, user interface design, and knowledge base construction. As such, this volume helps map out the future for all those involved in computer systems design.

Download or read book Algorithmic Learning Theory written by Shai Ben David and published by Springer Science & Business Media. This book was released on 2004-09-23 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic learning theory is mathematics about computer programs which learn from experience. This involves considerable interaction between various mathematical disciplines including theory of computation, statistics, and c- binatorics. There is also considerable interaction with the practical, empirical ?elds of machine and statistical learning in which a principal aim is to predict, from past data about phenomena, useful features of future data from the same phenomena. The papers in this volume cover a broad range of topics of current research in the ?eld of algorithmic learning theory. We have divided the 29 technical, contributed papers in this volume into eight categories (corresponding to eight sessions) re?ecting this broad range. The categories featured are Inductive Inf- ence, Approximate Optimization Algorithms, Online Sequence Prediction, S- tistical Analysis of Unlabeled Data, PAC Learning & Boosting, Statistical - pervisedLearning,LogicBasedLearning,andQuery&ReinforcementLearning. Below we give a brief overview of the ?eld, placing each of these topics in the general context of the ?eld. Formal models of automated learning re?ect various facets of the wide range of activities that can be viewed as learning. A ?rst dichotomy is between viewing learning as an inde?nite process and viewing it as a ?nite activity with a de?ned termination. Inductive Inference models focus on inde?nite learning processes, requiring only eventual success of the learner to converge to a satisfactory conclusion.

Download or read book Advances in Knowledge Acquisition written by Nigel Shadbolt and published by Springer Science & Business Media. This book was released on 1996-04-26 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the refereed proceedings of the 9th European Knowledge Acquisition Workshop, EKAW '96, held in Nottingham, UK, in May 1996. The 23 revised full papers included address the most relevant theoretical and applicational aspects of knowledge acquisition with a certain emphasis on the acquisition of knowledge for the modelling or automation of complex problem-solving behaviour. The volume is organized in sections on theoretical and general issues, eliciting knowledge from textual or other sources, data-mining, group elicitation, and planning.

Download or read book Learning Theory and Kernel Machines written by Bernhard Schölkopf and published by Springer. This book was released on 2003-11-11 with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.

Download or read book Learning Theory written by Hans Ulrich Simon and published by Springer. This book was released on 2006-09-29 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th Annual Conference on Learning Theory, COLT 2006, held in Pittsburgh, Pennsylvania, USA, June 2006. The book presents 43 revised full papers together with 2 articles on open problems and 3 invited lectures. The papers cover a wide range of topics including clustering, un- and semi-supervised learning, statistical learning theory, regularized learning and kernel methods, query learning and teaching, inductive inference, and more.